EP0999521A2 - Hochgenaue räumliche Unterpixelausrichtung von numerischen Bildern - Google Patents

Hochgenaue räumliche Unterpixelausrichtung von numerischen Bildern Download PDF

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Publication number
EP0999521A2
EP0999521A2 EP99308763A EP99308763A EP0999521A2 EP 0999521 A2 EP0999521 A2 EP 0999521A2 EP 99308763 A EP99308763 A EP 99308763A EP 99308763 A EP99308763 A EP 99308763A EP 0999521 A2 EP0999521 A2 EP 0999521A2
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EP
European Patent Office
Prior art keywords
test
image
images
pixel shift
test block
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EP99308763A
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English (en)
French (fr)
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EP0999521A3 (de
EP0999521B1 (de
Inventor
Shane Ching-Feng Hu
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Tektronix Inc
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Tektronix Inc
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
    • G06T7/32—Determination of transform parameters for the alignment of images, i.e. image registration using correlation-based methods

Definitions

  • the present invention relates to the matching of digital images, and more particularly to high precision sub-pixel spatial alignment of digital images.
  • Accurate spatial alignment of digital images is of fundamental importance to many applications.
  • One such application is the determination of picture quality using an instrument, such as the PQA200 Picture Quality Analyzer manufactured by Tektronix, Inc. of Wilsonville, Oregon, USA, where images from a reference video signal are compared with corresponding images from a test video signal that is a processed version of the reference video signal.
  • the better the spatial alignment between a reference image and a corresponding test image the more accurate the determination of the amount of degradation of the test video signal due to the processing.
  • the present invention provides for high precision sub-pixel spatial alignment of digital images using an iteration method and spatial resampling.
  • a high precision sub-pixel spatial alignment of digital images one form a reference video signal and another from a corresponding test video signal, uses an iterative process and incorporates spatial resampling along with basic correlation and estimation of fractional pixel shift.
  • the corresponding images from the reference and test video signals are captured and a test block is overlaid on them at the same locations to include texture from the images.
  • FFTs are performed within the test block in each image, and the FFTs are cross-correlated to develop a peak value representing a shift position between the images.
  • a curve is fitted to the peak and neighboring values to find the nearest integer pixel shift position.
  • the test block is shifted in the test image by the integer pixel shift position, and the FFT in the test image is repeated and correlated with the FFT from the reference image.
  • the curve fitting is repeated to obtain a fractional pixel shift position value that is combined with the integer pixel shift value to update the test block position again in the test image.
  • the steps are repeated until an end condition is achieved, at which point the value of the pixel shift position for the test block in the test image relative to the reference image is used to align the two images with high precision sub-pixel accuracy.
  • Fig. 1 is a block diagram view of a system for high precision sub-pixel spatial alignment of digital images according to the present invention.
  • Fig. 2 is an illustrative view of a comparison of an image from a reference video signal and an image from a corresponding test video signal to be spatially aligned with high precision sub-pixel accuracy according to the present invention.
  • Fig. 3 is a flow diagram view of a high precision sub-pixel spatial alignment algorithm according to the present invention.
  • Fig. 4 is an illustrative view of a cross-correlation surface showing a peak location for the high precision sub-pixel spatial alignment algorithm according to the present invention.
  • the video processing network 12 may include one or more compression/decompression passes.
  • the output from the video processing network 12 is input to a decoder or similar device 14 to provide a source of a test video signal.
  • the reference and test video signals are input to a video capture module 16 that captures corresponding images or frames from the two video signals.
  • the corresponding image pairs from the video capture module 16 are input to a high precision sub-pixel spatial alignment detect module 18 to determine a position shift between the images of the reference video signal and the images of the test video signal.
  • the position shift from the spatial alignment detect module 18 is input to a position shift module 20, which may be either in the reference or test signal path, to precisely align the image pairs with sub-pixel accuracy from the video capture module 16 for further processing, such as by a picture quality analyzer 22 .
  • Fig. 2 the reference and test images 24 , 26 are shown having some texture 25 , i.e., not a matte image.
  • the texture 25 has been shifted horizontally and/or vertically.
  • An arbitrary test region or block 28 is formed, shown in this example as a rectangle, having a reference point Xo, Yo and is overlaid on both the reference and test images.
  • the reference point and horizontal and vertical extents ⁇ X, ⁇ Y define the test region or block 28 .
  • the test region 28 is located where there is substantial texture 25 in the images.
  • a high precision sub-pixel spatial alignment algorithm is shown in Fig. 3.
  • An initialization module 30 provides the corresponding reference and test images together with a test block to a correlation measurement module 32.
  • the first step 34 in the initialization module 30 controls the video capture module 16 to capture corresponding reference and test images or frames from the reference and test video signals.
  • the second step 36 establishes a test block for overlaying on the respective images in an area that has significant texture 25 .
  • the first step 38 of the correlation measurement module 32 applies a fast Fourier transform (FFT) to the pixels of the images that lie within the test region.
  • a cross-correlation step 40 is then performed in the FFT domain.
  • FFT fast Fourier transform
  • FFT(corr) FFT(ref)*FFT(tst)
  • FFT -1 (corr) produces correlation coefficients for every shift point within the test region, which may be represented in the form of a surface 42 as shown in Fig. 4.
  • the position of a peak 44 in the surface 42 indicates the amount of shift in position between the reference and test images.
  • a curve-fit step 46 provides a nearest integer pixel shift position for the peak 44 based upon the coefficients for the peak position and the positions up, down, left and right from the peak position.
  • the pixel shift position from the correlation measure module 32 is input to an update shift position step 48 . For the first iteration only the nearest integer pixel shift position is used.
  • a testing step 50 checks the amount of position shift determined from the update shift position step 48 and the number of iterations against specified parameters to determine whether the spatial alignment algorithm is done. If the number of iterations is equal to the specified number, or the amount of update is less than a specified noise value, then the shift position value from the update step 48 is provided as an output pixel shift position and the algorithm ends. Otherwise a shift test block step 52 shifts the test region in the test image by the value from the update position step 48 so that the reference point is shifted to be X+X ⁇ , Y+Y ⁇ , where X ⁇ and Y ⁇ are the integer pixel shift position values.
  • the correlation module 32 is applied again to obtain a fractional pixel shift value in X and Y.
  • the FFT step 38 only the test image is processed after the initial iteration.
  • the FFT for the reference image does not change.
  • the fractional pixel shift value is used to update the shift position in the update step 48 so that the shift position becomes Xo+X ⁇ +X f , Yo+Y ⁇ +Y f . It has been found that for most practical applications two fractional pixel shift position iterations produce satisfactory results.
  • the final shift position value output from the spatial alignment detect module 18 is then used to spatially align the test and reference images as indicated above.
  • the present invention provides high precision sub-pixel spatial alignment of digital images by using an iterative process to cross-correlate FFTs for a test block from each image in order to find a peak representative of a shift position between the images, then by fitting a curve to the correlation coefficients to determine a nearest integer pixel shift position, updating the position of the test block in the test image and repeating until a specified number of iterations occurs or a change in fractional pixel shift position is less than a noise value.

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  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Image Analysis (AREA)
  • Image Processing (AREA)
  • Testing, Inspecting, Measuring Of Stereoscopic Televisions And Televisions (AREA)
EP99308763.4A 1998-11-05 1999-11-04 Hochgenaue räumliche Unterpixelausrichtung von numerischen Bildern Expired - Lifetime EP0999521B1 (de)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US09/186,761 US6483538B2 (en) 1998-11-05 1998-11-05 High precision sub-pixel spatial alignment of digital images
US186761 2000-03-03

Publications (3)

Publication Number Publication Date
EP0999521A2 true EP0999521A2 (de) 2000-05-10
EP0999521A3 EP0999521A3 (de) 2002-01-02
EP0999521B1 EP0999521B1 (de) 2016-10-26

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EP99308763.4A Expired - Lifetime EP0999521B1 (de) 1998-11-05 1999-11-04 Hochgenaue räumliche Unterpixelausrichtung von numerischen Bildern

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US (1) US6483538B2 (de)
EP (1) EP0999521B1 (de)
JP (1) JP3588290B2 (de)

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GB2394543A (en) * 2002-10-25 2004-04-28 Univ Bristol Positional measurement of a feature within an image
WO2006026214A1 (en) * 2004-08-31 2006-03-09 Hewlett-Packard Development Company L.P. Measuring sub-wavelength displacements
WO2007015271A1 (en) * 2005-08-02 2007-02-08 Fidia S.P.A. Precision displacement measuring system and method for industrial machines
WO2008128249A1 (en) * 2007-04-16 2008-10-23 Tektronix, Inc. Systems and methods for robust video temporal registration
US7763875B2 (en) 2005-09-07 2010-07-27 Romanov Nikolai L System and method for sensing position utilizing an uncalibrated surface
EP2173108A3 (de) * 2001-04-16 2013-01-02 KDDI Corporation Vorrichtung zur Überwachung der Qualität eines übertragenen Bilds

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WO2001075799A2 (en) * 2000-03-31 2001-10-11 British Telecommunications Public Limited Company Image processing
JP3846851B2 (ja) 2001-02-01 2006-11-15 松下電器産業株式会社 画像のマッチング処理方法及びその装置
US6993399B1 (en) * 2001-02-24 2006-01-31 Yesvideo, Inc. Aligning data streams
US7085431B2 (en) * 2001-11-13 2006-08-01 Mitutoyo Corporation Systems and methods for reducing position errors in image correlation systems during intra-reference-image displacements
GB0314161D0 (en) * 2003-06-18 2003-07-23 British Telecomm Edge analysis in video quality assessment
CA2646808C (en) * 2003-08-22 2013-01-22 Nippon Telegraph And Telephone Corporation Video aligning apparatus, video aligning method, and video quality assessing apparatus
JP3838513B2 (ja) * 2004-03-02 2006-10-25 Ｋｄｄｉ株式会社 伝送画質監視装置
US7586515B2 (en) * 2005-05-23 2009-09-08 Tektronix, Inc. Instrument for real-time video quality measurement
US7333865B1 (en) * 2006-01-03 2008-02-19 Yesvideo, Inc. Aligning data streams
AU2006203027B2 (en) * 2006-07-14 2009-11-19 Canon Kabushiki Kaisha Improved two-dimensional measurement system
JP4861109B2 (ja) * 2006-09-27 2012-01-25 富士通株式会社 画像データ処理装置、画像データ処理方法、画像データ処理プログラム、および、撮像装置
US7885480B2 (en) * 2006-10-31 2011-02-08 Mitutoyo Corporation Correlation peak finding method for image correlation displacement sensing
EP1988502A1 (de) * 2007-05-04 2008-11-05 Deutsche Thomson OHG Verfahren und Vorrichtung zum Abruf eines Testblocks aus einem blockweise gespeicherten Referenzbild
US8055101B2 (en) * 2008-04-29 2011-11-08 Adobe Systems Incorporated Subpixel registration
EP2114080A1 (de) * 2008-04-30 2009-11-04 Thomson Licensing Verfahren zur Beurteilung der Qualität einer gestörten Version einer Rahmensequenz
JP5415862B2 (ja) * 2009-07-29 2014-02-12 京セラ株式会社 動き量検出装置およびその方法、並びに撮像装置
US8792559B2 (en) * 2010-10-26 2014-07-29 Sony Corporation Method to improve accuracy and reliability of motion estimated with phase correlation
US8842735B2 (en) 2010-10-26 2014-09-23 Sony Corporation Method to improve detection of motion with phase correlation
US8896759B2 (en) 2010-10-26 2014-11-25 Sony Corporation Method to increase the accuracy of phase correlation motion estimation in low-bit-precision circumstances
GB201313682D0 (en) 2013-07-31 2013-12-18 Mbda Uk Ltd Method and apparatus for tracking an object
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US10015495B2 (en) * 2016-05-09 2018-07-03 Adobe Systems Incorporated Generating custom quantization tables for JPEG compression based on image content
US10360671B2 (en) * 2017-07-11 2019-07-23 Kla-Tencor Corporation Tool health monitoring and matching
JPWO2019092950A1 (ja) * 2017-11-13 2020-11-12 ソニー株式会社 画像処理装置、画像処理方法および画像処理システム
US10997712B2 (en) 2018-01-18 2021-05-04 Canon Virginia, Inc. Devices, systems, and methods for anchor-point-enabled multi-scale subfield alignment
US10997462B2 (en) 2018-04-04 2021-05-04 Canon Virginia, Inc. Devices, systems, and methods for clustering reference images for non-destructive testing
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Cited By (12)

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EP2173108A3 (de) * 2001-04-16 2013-01-02 KDDI Corporation Vorrichtung zur Überwachung der Qualität eines übertragenen Bilds
EP2173107A3 (de) * 2001-04-16 2013-10-16 KDDI Corporation Vorrichtung zur Überwachung der Qualität eines übertragenen Bilds
GB2394543A (en) * 2002-10-25 2004-04-28 Univ Bristol Positional measurement of a feature within an image
US8718403B2 (en) 2002-10-25 2014-05-06 Imetrum Limited Positional measurement of a feature within an image
EP1563252B1 (de) * 2002-10-25 2014-10-01 Imetrum Limited Messung der position eines objekts in einem bild und überprüfung einer struktur eines flugzeugs
WO2006026214A1 (en) * 2004-08-31 2006-03-09 Hewlett-Packard Development Company L.P. Measuring sub-wavelength displacements
US7283677B2 (en) 2004-08-31 2007-10-16 Hewlett-Packard Development Company, L.P. Measuring sub-wavelength displacements
WO2007015271A1 (en) * 2005-08-02 2007-02-08 Fidia S.P.A. Precision displacement measuring system and method for industrial machines
US7763875B2 (en) 2005-09-07 2010-07-27 Romanov Nikolai L System and method for sensing position utilizing an uncalibrated surface
WO2008128249A1 (en) * 2007-04-16 2008-10-23 Tektronix, Inc. Systems and methods for robust video temporal registration
US7978933B2 (en) 2007-04-16 2011-07-12 Tektronix, Inc. Systems and methods for robust video temporal registration
CN101682797B (zh) * 2007-04-16 2012-01-11 特克特朗尼克公司 用于稳健视频时间配准的系统和方法

Also Published As

Publication number Publication date
JP2000149029A (ja) 2000-05-30
JP3588290B2 (ja) 2004-11-10
US6483538B2 (en) 2002-11-19
EP0999521A3 (de) 2002-01-02
EP0999521B1 (de) 2016-10-26
US20020097342A1 (en) 2002-07-25

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